Open Access. Powered by Scholars. Published by Universities.®

Digital Commons Network™

Open Access. Powered by Scholars. Published by Universities.®

Research Collection School Of Computing and Information Systems

Discipline
Keyword
Publication Year
File Type

Articles 6481 - 6510 of 7017

Full-Text Articles in Entire DC Network

Synthesizing E-Government Stage Models – A Meta-Synthesis Based On Meta-Ethnography Approach, Keng Siau, Y. Long May 2005

Synthesizing E-Government Stage Models – A Meta-Synthesis Based On Meta-Ethnography Approach, Keng Siau, Y. Long

Research Collection School Of Computing and Information Systems

The growing interest in e-government raises the question of stages in e-government development. A few stage models for e-government have been proposed. Without a common e-government stage model, different research in e-government may be based on different stage models. This presents a difficulty in comparing and understanding different research results. In this research, we synthesize the existing e-government stage models so that there is a common frame of reference for researchers and practitioners in the area.


Dynamically Optimized Context In Recommender Systems, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang May 2005

Dynamically Optimized Context In Recommender Systems, Ghim-Eng Yap, Ah-Hwee Tan, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Traditional approaches to recommender systems have not taken into account situational information when making recommendations, and this seriously limits the relevance of the results. This paper advocates context-awareness as a promising approach to enhance the performance of recommenders, and introduces a mechanism to realize this approach. We present a framework that separates the contextual concerns from the actual recommendation module, so that contexts can be readily shared across applications. More importantly, we devise a learning algorithm to dynamically identify the optimal set of contexts for a specific recommendation task and user. An extensive series of experiments has validated that our …


Leveraging Global Resources: A Distributed Process Maturity Framework For Software Product Development, Narayan Ramasubbu, M. S. Krishnan, Prasad Kompalli May 2005

Leveraging Global Resources: A Distributed Process Maturity Framework For Software Product Development, Narayan Ramasubbu, M. S. Krishnan, Prasad Kompalli

Research Collection School Of Computing and Information Systems

Distributed software development is pervasive in the software industry today as companies vie to leverage global resources. However, popular quality and process frameworks don?t specifically address the key processes needed for managing distributed software development. This practitioner-oriented, evolutionary process maturity framework for globally distributed software development features 24 new key process areas essential for managing distributed software product development and for continuously improving product management capabilities. An assessment survey helps practitioners implement the framework. In this article, the authors detail the framework and assessment survey, as well as report their experiences implementing the framework at a leading global firm. The …


Mining Social Network From Spatio-Temporal Events, Hady Wirawan Lauw, Ee Peng Lim, Teck Tim Tan, Hwee Hwa Pang Apr 2005

Mining Social Network From Spatio-Temporal Events, Hady Wirawan Lauw, Ee Peng Lim, Teck Tim Tan, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Knowing patterns of relationship in a social network is very useful for law enforcement agencies to investigate collaborations among criminals, for businesses to exploit relationships to sell products, or for individuals who wish to network with others. After all, it is not just what you know, but also whom you know, that matters. However, finding out who is related to whom on a large scale is a complex problem. Asking every single individual would be impractical, given the huge number of individuals and the changing dynamics of relationships. Recent advancement in technology has allowed more data about activities of individuals …


Walverine: A Walrasian Trading Agent, Shih-Fen Cheng, Evan Leung, Kevin M. Lochner, Kevin O'Malley, Daniel M. Reeves, Julian L. Schvartzman, Michael P. Wellman Apr 2005

Walverine: A Walrasian Trading Agent, Shih-Fen Cheng, Evan Leung, Kevin M. Lochner, Kevin O'Malley, Daniel M. Reeves, Julian L. Schvartzman, Michael P. Wellman

Research Collection School Of Computing and Information Systems

TAC-02 was the third in a series of Trading Agent Competition events fostering research in automating trading strategies by showcasing alternate approaches in an open-invitation market game. TAC presents a challenging travel-shopping scenario where agents must satisfy client preferences for complementary and substitutable goods by interacting through a variety of market types. Michigan's entry, Walverine, bases its decisions on a competitive (Walrasian) analysis of the TAC travel economy. Using this Walrasian model, we construct a decision-theoretic formulation of the optimal bidding problem, which Walverine solves in each round of bidding for each good. Walverine's optimal bidding approach, as well as …


Privacy And Ownership Preserving Of Outsourced Medical Data, Elisa Bertino, Beng Chin Ooi, Yanjiang Yang, Robert H. Deng Apr 2005

Privacy And Ownership Preserving Of Outsourced Medical Data, Elisa Bertino, Beng Chin Ooi, Yanjiang Yang, Robert H. Deng

Research Collection School Of Computing and Information Systems

The demand for the secondary use of medical data is increasing steadily to allow for the provision of better quality health care. Two important issues pertaining to this sharing of data have to be addressed: one is the privacy protection for individuals referred to in the data; the other is copyright protection over the data. In this paper, we present a unified framework that seamlessly combines techniques of binning and digital watermarking to attain the dual goals of privacy and copyright protection. Our binning method is built upon an earlier approach of generalization and suppression by allowing a broader concept …


Integrating User Feedback Log Into Relevance Feedback By Coupled Svm For Content-Based Image Retrieval, Steven C. H. Hoi, Michael R. Lyu, Rong Jin Apr 2005

Integrating User Feedback Log Into Relevance Feedback By Coupled Svm For Content-Based Image Retrieval, Steven C. H. Hoi, Michael R. Lyu, Rong Jin

Research Collection School Of Computing and Information Systems

Relevance feedback has been shown as an important tool to boost the retrieval performance in content-based image retrieval. In the past decade, various algorithms have been proposed to formulate relevance feedback in contentbased image retrieval. Traditional relevance feedback techniques mainly carry out the learning tasks by focusing lowlevel visual features of image content with little consideration on log information of user feedback. However, from a long-term learning perspective, the user feedback log is one of the most important resources to bridge the semantic gap problem in image retrieval. In this paper we propose a novel technique to integrate the log …


Ais Sighci Position Paper, Dennis Galletta, Ping Zhang, Fiona Fui-Hoon Nah Apr 2005

Ais Sighci Position Paper, Dennis Galletta, Ping Zhang, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

The upcoming ACM SIGCHI Development Consortium is aimed at meeting the needs of multidisciplinary professionals that must choose among a variety of professional associations and their events. The position of AIS' (Association for Information Systems) SIGHCI is that the main problem lies in the deep chasms that separate the literatures of the related disciplines, and the solution is to provide an umbrella organization that enables a more organized federation of disciplines, groups, and associations. Problems identified include differences in terminology, competition for scarce resources, differences in how publications in various outlets are valued, and confusion about where should be the …


Proactive Caching For Spatial Queries In Mobile Environments, Haibo Hu, Jianliang Xu, Wing Sing Wong, Baihua Zheng, Dik Lun Lee, Wang-Chien Lee Apr 2005

Proactive Caching For Spatial Queries In Mobile Environments, Haibo Hu, Jianliang Xu, Wing Sing Wong, Baihua Zheng, Dik Lun Lee, Wang-Chien Lee

Research Collection School Of Computing and Information Systems

Semantic caching enables mobile clients to answer spatial queries locally by storing the query descriptions together with the results. However, it supports only a limited number of query types, and sharing results among these types is difficult. To address these issues, we propose a proactive caching model which caches the result objects as well as the index that supports these objects as the results. The cached index enables the objects to be reused for all common types of queries. We also propose an adaptive scheme to cache such an index, which further optimizes the query response time for the best …


Predictive Neural Networks For Gene Expression Data Analysis, Ah-Hwee Tan, Hong Pan Apr 2005

Predictive Neural Networks For Gene Expression Data Analysis, Ah-Hwee Tan, Hong Pan

Research Collection School Of Computing and Information Systems

Gene expression data generated by DNA microarray experiments have provided a vast resource for medical diagnosis and disease understanding. Most prior work in analyzing gene expression data, however, focuses on predictive performance but not so much on deriving human understandable knowledge. This paper presents a systematic approach for learning and extracting rule-based knowledge from gene expression data. A class of predictive self-organizing networks known as Adaptive Resonance Associative Map (ARAM) is used for modelling gene expression data, whose learned knowledge can be transformed into a set of symbolic IF-THEN rules for interpretation. For dimensionality reduction, we illustrate how the system …


Effect Of Training Datasets On Support Vector Machine Prediction Of Protein-Protein Interactions, Siaw Ling Lo, Cong Zhong Cai, Maxey Chung, Yu Zong Chen Mar 2005

Effect Of Training Datasets On Support Vector Machine Prediction Of Protein-Protein Interactions, Siaw Ling Lo, Cong Zhong Cai, Maxey Chung, Yu Zong Chen

Research Collection School Of Computing and Information Systems

Knowledge of protein-protein interaction is useful for elucidating protein function via the concept of 'guilt-by-association'. A statistical learning method, Support Vector Machine (SVM), has recently been explored for the prediction of protein-protein interactions using artificial shuffled sequences as hypothetical noninteracting proteins and it has shown promising results (Bock, J. R., Gough, D. A., Bioinformatics 2001, 17, 455-460). It remains unclear however, how the prediction accuracy is affected if real protein sequences are used to represent noninteracting proteins. In this work, this effect is assessed by comparison of the results derived from the use of real protein sequences with that derived …


Scheduling Queries To Improve The Freshness Of A Website, Haifeng Liu, Wee-Keong Ng, Ee Peng Lim Mar 2005

Scheduling Queries To Improve The Freshness Of A Website, Haifeng Liu, Wee-Keong Ng, Ee Peng Lim

Research Collection School Of Computing and Information Systems

The World Wide Web is a new advertising medium that corporations use to increase their exposure to consumers. Very large websites whose content is derived from a source database need to maintain a freshness that reflects changes that are made to the base data. This issue is particularly significant for websites that present fast-changing information such as stock-exchange information and product information. In this article, we formally define and study the freshness of a website that is refreshed by a scheduled set of queries that fetch fresh data from the databases. We propose several online-scheduling algorithms and compare the performance …


Mastaq: A Middleware Architecture For Sensor Applications With Statistical Quality Constraints, Inseok Hwang, Qi Han, Archan Misra Mar 2005

Mastaq: A Middleware Architecture For Sensor Applications With Statistical Quality Constraints, Inseok Hwang, Qi Han, Archan Misra

Research Collection School Of Computing and Information Systems

We present the design goals and functional components of MASTAQ, a data management middleware for pervasive applications that utilize sensor data. MASTAQ allows applications to specify their quality-of information (QoI) preferences (in terms of statistical metrics over the data) independent of the underlying network topology. It then achieves energy efficiency by adaptively activating and querying only the subset of sensor nodes needed to meet the target QoI bounds. We also present a closed-loop feedback mechanism based on broadcasting of activation probabilities, which allows MASTAQ to activate the appropriate number of sensors without requiring any inter-sensor coordination or knowledge of the …


Evaluation Of Mpeg-4 Ipmp Extension, Hwee Hwa Pang, Yongdong Wu Mar 2005

Evaluation Of Mpeg-4 Ipmp Extension, Hwee Hwa Pang, Yongdong Wu

Research Collection School Of Computing and Information Systems

MPEG-4 IPMPX (intellectual property management and protection extension) is the latest ISO standard which provides a flexible framework for protecting MPEG streams. The message mechanism of IPMPX enables interoperability among IPMPX-compliant devices no matter which protection methods are embedded. This paper highlights several problems in the message syntax of IPMPX: the tool delivery message IPMP_ToolES_AU is vulnerable to network attack, the authentication message IMP_Mutual_Authentication is incapable of defending against forgery attack, and the configuration message IPMP_SelectiveDecrptionInit is ambiguous and redundant. We propose a number of remedies to those problems, which can be incorporated into a corrigenda to improve the present …


Video Summarization And Scene Detection By Graph Modeling, Chong-Wah Ngo, Yu-Fei Ma, Hong-Jiang Zhang Feb 2005

Video Summarization And Scene Detection By Graph Modeling, Chong-Wah Ngo, Yu-Fei Ma, Hong-Jiang Zhang

Research Collection School Of Computing and Information Systems

In this paper, we propose a unified approach for video summarization based on the analysis of video structures and video highlights. Two major components in our approach are scene modeling and highlight detection. Scene modeling is achieved by normalized cut algorithm and temporal graph analysis, while highlight detection is accomplished by motion attention modeling. In our proposed approach, a video is represented as a complete undirected graph and the normalized cut algorithm is carried out to globally and optimally partition the graph into video clusters. The resulting clusters form a directed temporal graph and a shortest path algorithm is proposed …


The Value Of Mobile Applications: A Utility Company Study, Fiona Fui-Hoon Nah, Keng Siau, Hong Sheng Feb 2005

The Value Of Mobile Applications: A Utility Company Study, Fiona Fui-Hoon Nah, Keng Siau, Hong Sheng

Research Collection School Of Computing and Information Systems

The value proposition of mobile applications i.e. the net value of the benefits and costs associated with the adoption and adaptation of mobile applications is discussed. A means-ends network that depicts the fundamental relationships among the objectives such as efficiency, effectiveness, customer satisfaction, security, cost, and employee acceptance, was developed. The network is useful to researchers as it highlights the issues, concerns, and values of mobile applications. The network help the managers and practitioners to achieve their companies' objectives of implementing mobile and wireless applications.


Linear Correlation Discovery In Databases: A Data Mining Approach, Cecil Chua, Roger Hsiang-Li Chiang, Ee Peng Lim Jan 2005

Linear Correlation Discovery In Databases: A Data Mining Approach, Cecil Chua, Roger Hsiang-Li Chiang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Very little research in knowledge discovery has studied how to incorporate statistical methods to automate linear correlation discovery (LCD). We present an automatic LCD methodology that adopts statistical measurement functions to discover correlations from databases’ attributes. Our methodology automatically pairs attribute groups having potential linear correlations, measures the linear correlation of each pair of attribute groups, and confirms the discovered correlation. The methodology is evaluated in two sets of experiments. The results demonstrate the methodology’s ability to facilitate linear correlation discovery for databases with a large amount of data.


Special Section: Human-Computer Interaction Research In Management Information Systems, Ping Zhang, Fiona Fui-Hoon Nah, Izak Benbasat Jan 2005

Special Section: Human-Computer Interaction Research In Management Information Systems, Ping Zhang, Fiona Fui-Hoon Nah, Izak Benbasat

Research Collection School Of Computing and Information Systems

No abstract provided.


Partnering For Perfection: An Economics Perspective On B2b Electronic Market Strategic Alliances, Qizhi Dai, Robert J. Kauffman Jan 2005

Partnering For Perfection: An Economics Perspective On B2b Electronic Market Strategic Alliances, Qizhi Dai, Robert J. Kauffman

Research Collection School Of Computing and Information Systems

New technological innovations have made it possible for new intermediaries to create value in business processes that involve the procurement of manufacturing and services supplies. Associated with these innovations is the emergence of business-to-business (B2B) electronic markets. These act as digital intermediaries that aim to reduce the transaction costs and mitigate the risks inherent in procurement. They improve buyers’ capabilities to search for attractive prices and also serve to increase the liquidity of sellers’ products. In this chapter, the authors explore the evolution of B2B e-market firms in terms of the strategies they employ to “perfect” their value propositions and …


Ontology-Assisted Mining Of Rdf Documents, Tao Jiang, Ah-Hwee Tan Jan 2005

Ontology-Assisted Mining Of Rdf Documents, Tao Jiang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Resource description framework (RDF) is becoming a popular encoding language for describing and interchanging metadata of web resources. In this paper, we propose an Apriori-based algorithm for mining association rules (AR) from RDF documents. We treat relations (RDF statements) as items in traditional AR mining to mine associations among relations. The algorithm further makes use of a domain ontology to provide generalization of relations. To obtain compact rule sets, we present a generalized pruning method for removing uninteresting rules. We illustrate a potential usage of AR mining on RDF documents for detecting patterns of terrorist activities. Experiments conducted based on …


Technology Competition And Optimal Investment Timing: A Real Options Perspective, Robert J. Kauffman, X. Li Jan 2005

Technology Competition And Optimal Investment Timing: A Real Options Perspective, Robert J. Kauffman, X. Li

Research Collection School Of Computing and Information Systems

Companies often choose to defer irreversible investments to maintain valuable managerial flexibility in an uncertain world. For some technology-intensive projects, technology uncertainty plays a dominant role in affecting investment timing. This article analyzes the investment timing strategy for a firm that is deciding about whether to adopt one or the other of two incompatible and competing technologies.We develop a continuous-time stochastic model that aids in the determination of optimal timing for managerial adoption within the framework of real options theory. The model captures the elements of the decision-making process in such a way so as to provide managerial guidance in …


Optimal Location Of Intermodal Freight Hubs, Illia Racunica, Laura Wynter Jan 2005

Optimal Location Of Intermodal Freight Hubs, Illia Racunica, Laura Wynter

Research Collection School Of Computing and Information Systems

We present an optimization model that has been developed to address the problem of increasing the share of rail in intermodal transport through the use of hub-and-spoke type networks for freight rail. The model defined is a generalization of the hub location problem in that it allows for non-linear and concave cost functions on different segments. A linearization procedure along with two efficient variable-reduction heuristics was developed for its resolution, making use of recent results on polyhedral properties of this class of problems. Computational experience and a qualitative analysis from a case study on the Alpine freight network is provided.


Applying Scenario-Based Design And Claim Analysis To The Design Of A Digital Library Of Geography Examination Resources, Yin-Leng Theng, Dion Hoe-Lian Goh, Ee Peng Lim, Zehua Liu, Ming Yin, Natalie Lee-San Pang, Patricia Bao-Bao Wong Jan 2005

Applying Scenario-Based Design And Claim Analysis To The Design Of A Digital Library Of Geography Examination Resources, Yin-Leng Theng, Dion Hoe-Lian Goh, Ee Peng Lim, Zehua Liu, Ming Yin, Natalie Lee-San Pang, Patricia Bao-Bao Wong

Research Collection School Of Computing and Information Systems

This paper describes the application of Carroll’s scenario-based design and claims analysis as a means of refinement to the initial design of a digital library of geographical resources (GeogDL) to prepare Singapore students to take a national examination in geography. GeogDL is built on top of G-Portal, a digital library providing services over geospatial and georeferenced Web content. Beyond improving the initial design of GeogDL, a main contribution of the paper is making explicit the use of Carroll’s strong theory-based but undercapitalized scenario-based design and claims analysis that inspired recommendations for the refinement of GeogDL. The paper concludes with an …


A Multi-Agent Approach For Solving Optimization Problems Involving Expensive Resources, Hoong Chuin Lau, H. Wang Jan 2005

A Multi-Agent Approach For Solving Optimization Problems Involving Expensive Resources, Hoong Chuin Lau, H. Wang

Research Collection School Of Computing and Information Systems

In this paper, we propose a multi-agent approach for solving a class of optimization problems involving expensive resources, where monolithic local search schemes perform miserably. More specifically, we study the class of bin-packing problems. Under our proposed Fine-Grained Agent System scheme, rational agents work both collaboratively and selfishly based on local search and mimic physics-motivated systems. We apply our approach to a generalization of bin-packing - the Inventory Routing Problem with Time Windows - which is an important logistics problem, and demonstrate the efficiency and effectiveness of our approach.


Systems Analysis And Design: Should We Be Researching What We Teach?, A. Bajaj, D. Batra, A. Hevner, J. Parsons, Keng Siau Jan 2005

Systems Analysis And Design: Should We Be Researching What We Teach?, A. Bajaj, D. Batra, A. Hevner, J. Parsons, Keng Siau

Research Collection School Of Computing and Information Systems

A guiding premise of academic scholarship is that knowledge gained from first-hand research experience is disseminated to students via the classroom. However, that valuable connection is lost when professors are not researching what they teach. In this paper, we explore issues of mismatch between teaching and research in the Information Systems (IS) discipline. Specifically, while systems analysis and design (SA&D) is an integral topic in IS curricula, this topic is the research specialty of few IS professors. This situation is reflected by the low number of research publications in this area; particularly in the leading mainstream IS journals. We characterize …


Robust Temporal Constraint Networks, Hoong Chuin Lau, Thomas Ou, Melvyn Sim Jan 2005

Robust Temporal Constraint Networks, Hoong Chuin Lau, Thomas Ou, Melvyn Sim

Research Collection School Of Computing and Information Systems

In this paper, we propose the Robust Temporal Constraint Network (RTCN) model for simple temporal constraint networks where activity durations are bounded by random variables. The problem is to determine whether such temporal network can be executed with failure probability less than a given 0 ≤ E ≤ 1 for each possible instantiation of the random variables, and if so. how one might find a feasible schedule with each given instantiation. The advantage of our model is that one can vary the value of ∊ to control the level of conservativeness of the solution. We present a computationally tractable and …


Justilm: Few-Shot Justification Generation For Explainable Fact-Checking Of Real-World Claims, Fengzhu Zeng, Wei Gao Dec 2004

Justilm: Few-Shot Justification Generation For Explainable Fact-Checking Of Real-World Claims, Fengzhu Zeng, Wei Gao

Research Collection School Of Computing and Information Systems

Justification is an explanation that supports the verdict assigned to a claim in fact-checking. However, the task of justification generation is previously oversimplified as summarization of fact-check article authored by professional checkers. In this work, we propose a realistic approach to generate justification based on retrieved evidence. We present a new benchmark dataset called ExClaim for Explainable Claim verification, and introduce JustiLM, a novel few-shot retrieval-augmented language model to learn justification generation by leveraging fact-check articles as auxiliary resource during training. Our results show that JustiLM outperforms in-context learning (ICL)-enabled LMs including Flan-T5 and Llama2, and the retrieval-augmented model Atlas …


Method For Identifying Individuals, Manoj Thulasidas Dec 2004

Method For Identifying Individuals, Manoj Thulasidas

Research Collection School Of Computing and Information Systems

A method and system for identifying a subject comprises obtaining a digitised recording of an electrocardiogram measurement of the subject to be identified, the digitised recording being a cyclic waveform having a peak amplitude. The digitised recording is normalised to reduce variations due to physiological effects, and the normalised recording is processed to determine a feature vector in the frequency domain. The distance between the determined feature vector and a predetermined feature vector is measured to identify the subject.


Supporting Field Study With Personalized Project Spaces In A Geographical Digital Library, Ee Peng Lim, Aixin Sun, Zehua Liu, John Hedberg, Chew-Hung Chang, Tiong-Sa Teh, Dion Hoe-Lian Goh, Yin-Leng Theng Dec 2004

Supporting Field Study With Personalized Project Spaces In A Geographical Digital Library, Ee Peng Lim, Aixin Sun, Zehua Liu, John Hedberg, Chew-Hung Chang, Tiong-Sa Teh, Dion Hoe-Lian Goh, Yin-Leng Theng

Research Collection School Of Computing and Information Systems

Digital libraries have been rather successful in supporting learning activities by providing learners with access to information and knowledge. However, this level of support is passive to learners and interactive and collaborative learning cannot be easily achieved. In this paper, we study how digital libraries could be extended to serve a more active role in collaborative learning activities. We focus on developing new services to support a common type of learning activity, field study, in a geospatial context. We propose the concept of personal project space that allows individuals to work in their personalized environment with a mix of private …


High Performance P300 Speller For Brain-Computer Interface, Cuntai Guan, Manoj Thulasidas, Jiankang Wu Dec 2004

High Performance P300 Speller For Brain-Computer Interface, Cuntai Guan, Manoj Thulasidas, Jiankang Wu

Research Collection School Of Computing and Information Systems

P300 speller is a communication tool with which one can input texts or commands to a computer by thought. The amplitude of the P300 evoked potential is inversely proportional to the probability of infrequent or task-related stimulus. In existing P300 spellers, rows and columns of a matrix are intensified successively and randomly, resulting in a stimulus frequency of 1/N (N is the number of rows or columns of the matrix). We propose a new paradigm to display each single character randomly and individually (therefore reducing the stimulus frequency to 1/(N*N)). On-line experiments showed that this new speller significantly improved the …